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Regional heterogeneous drivers of electricity demand in Saudi Arabia: Modeling regional residential electricity demand

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  • Mikayilov, Jeyhun I.
  • Darandary, Abdulelah
  • Alyamani, Ryan
  • Hasanov, Fakhri J.
  • Alatawi, Hatem

Abstract

This study investigates the drivers of residential electricity demand in Saudi Arabia at a regional level for the period 1990–2018 using Structural Time Series Modeling. We find that Saudi Arabia's two waves of energy price reforms in 2016 and 2018 have had different impacts on residential electricity consumption across its regions. The empirical estimation results show that the long-run price responses of residential electricity demand vary across regions: from −0.20 in the Central region to −0.46 in the Eastern region. The short-run elasticities are −0.10 for the Central and Western regions, −0.15 in the Southern region, while the Eastern region's demand does not respond to price changes in the short run. The long run income elasticities of the regions' residential electricity demand also differ considerably: from 1.02 in the Western region to 0.27 in the Eastern region. The short-run income elasticities are 0.14 and 0.43 for the Eastern and Western regions, respectively while the residential electricity demand in the Central and Southern regions' does not react to income changes. We further estimate that hot weather conditions significantly impact all regions' residential electricity demand. Finally, we find that all regions saw some efficiency improvements in light of the energy price reforms, although there is a room for further improvements. The findings of the study can be useful for policymakers through the ways that we discussed in the paper.

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  • Mikayilov, Jeyhun I. & Darandary, Abdulelah & Alyamani, Ryan & Hasanov, Fakhri J. & Alatawi, Hatem, 2020. "Regional heterogeneous drivers of electricity demand in Saudi Arabia: Modeling regional residential electricity demand," Energy Policy, Elsevier, vol. 146(C).
    • Handle: RePEc:eee:enepol:v:146:y:2020:i:c:s0301421520305176
    DOI: 10.1016/j.enpol.2020.111796
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    Cited by:

    1. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    2. Liddle, Brantley, 2023. "Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying," Energy Economics, Elsevier, vol. 124(C).
    3. Belaïd, Fateh & Mikayilov, Jeyhun I., 2024. "Closing the Efficiency Gap: Insights into curbing the direct rebound effect of residential electricity consumption in Saudi Arabia," Energy Economics, Elsevier, vol. 135(C).
    4. Darandary, Abdulelah & Mikayilov, Jeyhun I. & Soummane, Salaheddine, 2024. "Impacts of electricity price reform on Saudi regional fuel consumption and CO2 emissions," Energy Economics, Elsevier, vol. 131(C).
    5. Fahad Saleh Al-Ismail & Md Shafiul Alam & Md Shafiullah & Md Ismail Hossain & Syed Masiur Rahman, 2023. "Impacts of Renewable Energy Generation on Greenhouse Gas Emissions in Saudi Arabia: A Comprehensive Review," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    6. Carlos Enrique Carrasco-Gutierrez & Philipp Ehrl, 2023. "Regional Estimates of Residential Electricity Demand in Brazil," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 465-476, January.
    7. Salaheddine Soummane & F. Ghersi, 2022. "Projecting Saudi sectoral electricity demand in 2030 using a computable general equilibrium model," Post-Print hal-03500916, HAL.
    8. Jumah Ahmad Alzyadat, 2022. "The Price and Income Elasticity of Demand for Natural Gas Consumption in Saudi Arabia," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 357-363, November.
    9. Salma Hamad Almuhaini & Nahid Sultana, 2023. "Bayesian-Optimization-Based Long Short-Term Memory (LSTM) Super Learner Approach for Modeling Long-Term Electricity Consumption," Sustainability, MDPI, vol. 15(18), pages 1-23, September.
    10. Salma Hamad Almuhaini & Nahid Sultana, 2023. "Forecasting Long-Term Electricity Consumption in Saudi Arabia Based on Statistical and Machine Learning Algorithms to Enhance Electric Power Supply Management," Energies, MDPI, vol. 16(4), pages 1-28, February.
    11. Gasim, Anwar A. & Agnolucci, Paolo & Ekins, Paul & De Lipsis, Vincenzo, 2023. "Modeling final energy demand and the impacts of energy price reform in Saudi Arabia," Energy Economics, Elsevier, vol. 120(C).

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